rag-101

Building Your First RAG Pipeline

Consider giving this repo a ✨! Thanks!!!

Here's a link to the YouTube video explaining this setup in greater detail:

Prerequisites

You need to have the following tools installed:

• Poetry
• Inferix or any OpenAI compatible API.

Environment Setup

1. Setup poetry

# To setup poetry
poetry install

2. Install Inferix (OpenAI compatible API)

Note: You can use any OpenAI compatible backend or simply use OpenAI itself.

• Feel free to use any OpenAI compatible API.
• Make sure you have Ollama installed.
• Make sure you have pulled a model. I recommend Qwen 2.5 32B.
• Use this guide to setup inferix to host a OpenAI compatible API capable of function calling.

3. Set the environment variables

• OPENAI_API_KEY
• OPENAI_API_BASE_URL

You'll probably have to change the models being used everywhere as well

Run the app

We've got a few scripts in this project:

1. poetry run 01 - Making a simple LLM call using the openai sdk.
2. poetry run 02 - Demonstration of how in-context learning can really personalize AI responses.
3. poetry run 03 - Demonstration of how vector/similarity search works.
4. poetry run 04 - This script will fail. The chunks generated are too large for embedding to work.
5. poetry run 05 - A basic RAG pipeline with recursive text splitting.
6. poetry run 06 - A slightly better RAG pipeline using Markdown based splitting.